A method and device for vehicle color recognition based on deep learning

Abstract

The invention discloses a vehicle color recognition method and device based on deep learning, including: inputting vehicle images as test samples and training samples and performing preprocessing; using the training samples to train a convolutional neural network to extract deep color features; using deep color features Train a classifier to recognize the vehicle color of the test sample. The invention improves the accuracy rate of vehicle color recognition, simplifies structural parameters and eliminates overfitting.

Description

technical field [0001] The present invention relates to the field of machine learning, in particular, to a vehicle color recognition method and device based on deep learning. Background technique [0002] Traffic order management is an important part of road traffic management. With the rapid increase in the number of motor vehicles and drivers, and the drivers' legal safety awareness is generally low, there are more and more risks and uncertainties affecting road traffic safety. Continuously emerging, traffic police, public security and other fields are facing severe challenges and situations, increasing the difficulty of road traffic order management. The license plate has long been one of the core research objects in the field of intelligent transportation systems. In the face of partial occlusion, viewing angle changes, noise, blurring and other conditions, the license plate is not always completely visible. In contrast, the color of the car body occupies the main part ...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problems of low accuracy rate, parameter redundancy and overfitting of vehicle color recognition in the prior art, there is currently no effective solution

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